LSMS Integrated Surveys on Agriculture Ethiopia Socioeconomic Survey (ESS) 2015/2016
|
|
- Adelia Cunningham
- 6 years ago
- Views:
Transcription
1 LSMS Integrated Surveys on Agriculture Ethiopia Socioeconomic Survey (ESS) 2015/2016 A Report by the Central Statistical Agency of Ethiopia in Collaboration with the National Bank of Ethiopia and the World Bank February 2017
2 LSMS Integrated Surveys on Agriculture Ethiopia Socioeconomic Survey (ESS) 2015/2016 Central Statistical Agency and Living Standards Measurement Study (LSMS), World Bank February 2017
3 Acknowledgments The Central Statistical Agency of Ethiopia and the World Bank Living Standards Measurement Study (LSMS) team would like to thank the Bill and Melinda Gates Foundation for financial support.
4 Table of Contents Acronyms... Executive Summary... vii ix Chapter 1: Survey Objectives, Design and Implementation Objectives Survey Design Instruments, Training and Fieldwork Data Entry and Cleaning Organization of the Survey Report... 4 Chapter 2: Demography, Education and Health Household Demography Education Health Chapter 3: Housing Characteristics and Household Assets Housing Characteristics: Ownership, Structure and Facilities Household Assets Chapter 4: Agriculture Agricultural Households Crop Farming Livestock... 32
5 iv Ethiopia Socioeconomic Survey Chapter 5: Non-Farm Enterprises, Other Income, and Assistance Non-Farm Enterprises Other Income Sources Assistance from Government and Nongovernmental Agencies Chapter 6: Time Use and Labor The ESS Time Use Data Time Spent on Collecting Water and Fuelwood Time Spent on Agricultural Activities Time Spent on Non-Farm Enterprise Activities Time Spent on Casual, Part-Time and Temporary Work Time Spent on Work for Salary and Wages Time Spent on Apprentice and Unpaid Work Chapter 7: Consumption, Food Security and Shocks Consumption Food Security Shocks and Coping Mechanisms Chapter 8: Finance: Banking, Savings, Insurance and Credit Introduction Account Owners Types of Financial Institutions and Services Knowledge of Financial Procedures Savings Reasons for Saving Method and Frequency of Saving Capacity to Save... 57
6 Table of Contents v 8.9 Insurance Coverage Reasons for Not Using Formal Insurance Services Financial Knowledge and Preference Loan Source Loan Amount and Reasons... 61
7
8 Acronyms AgSS CAPI CSA EA ERSS ESS Annual Agricultural Sample Survey Computer Assisted Personal Interviewing Central Statistical Agency Enumeration Areas Ethiopia Rural Socioeconomic Survey Ethiopia Socioeconomic Survey LSMS Living Standards Measurement Study LSMS-ISA Living Standards Measurement Study- Integrated Surveys on Agriculture NFE PSNP SACCO Non-Farm Enterprises Productive Safety Net Program Savings and Credit Cooperative Organization
9
10 Executive Summary Survey Objectives and Design: The Ethiopia Socioeconomic Survey (ESS) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture program. The objectives include the development of an innovative model for collecting agricultural data, interinstitutional collaboration, and comprehensive analysis of welfare indicators and socioeconomic characteristics. ESS is a nationally representative survey of over 5,000 households living in rural and urban areas. It is integrated with the CSA s Annual Agricultural Sample Survey (AgSS); the rural households included in the ESS are a sub-sample of the AgSS sample households. ESS is a panel survey. The first and the second waves were implemented in and in respectively. The third wave was implemented in This report compiles a set of basic statistics from the third wave. The statistics presented here are a highlight of very few selected indicators. The results are disaggregated by location variables region and place of residence. Place of residence includes rural, small towns and large town areas. When applicable, some results are presented by gender and age group. In some tables, the number of observations is too small to interpret the results. Demographic Characteristics: The survey finds that average household size in rural, small town and large town areas is 5.2 and 4.3 and 3.7 persons per household respectively. Average dependency ratio at the country level is 88 percent. It is higher in rural areas (100 percent) than in small town (69 percent) and large town areas (48 percent). Education: Educational outcome of household members (age 5 years and above) is captured in the survey by self-reported literacy, attainment, attendance/ enrollment, and constraints such as proximity to primary and secondary schools and school expenses. The survey finds that the literacy level (for reading and writing in any language) is 64 percent for males while it is 48 percent for females. For school age population (ages 7 18 years), approximately 30 percent of boys and girls are not in school. Primary and secondary enrollment rates are similar for both sexes. Approximately 64 percent are enrolled in primary schools and the remaining few (less than 6 percent) are enrolled in secondary schools. Health: Survey questions gathered information on prevalence of illness, disability, health care facility utilization, and child anthropometrics. Prevalence of selfreported illness for the four weeks preceding the survey is 9 percent for males and 12 percent for females. Disability, measured by difficulties of hearing, seeing, walking or climbing, remembering or concentrating, self-care including washing, dressing and feeding, and communicating or understanding, is higher for the oldest group (ages 51 and above), with females exhibiting more disabilities than males in that age group. The overall health care utilization for treatment or checkups (measured over the four weeks preceding the survey) is approximately 8 percent for males and 11 percent for females. The most important facilities visited are health centers (40 percent) followed by clinics (21 percent) and hospitals (15 percent). People also visited pharmacies (10 percent), health posts (6 percent), traditional healers (5 percent), and others (4 percent). However,
11 x Ethiopia Socioeconomic Survey not all went to a health facility. The reasons for not seeking consultation include distance and affordability. However, the most important reason is that people do not normally go to health facilities for regular checkups. Child anthropometrics results, for children ages 5 59 months, show that, at the national level, child stunting, underweight and wasting are 42 percent, 24 percent and 10 percent respectively. Child malnutrition rates are higher in rural than in urban areas. Housing Characteristics: The survey collected information on housing tenure and characteristics as well as other assets that are owned by the household. The finding shows that about 80 percent of households live in their own houses. The rest live in either rented houses (13 percent) or houses obtained in other arrangements (5 percent). A number of housing quality indicators show that the majority live in congested houses that have poor flooring, walls and roofing structures, and lack basic utilities. As expected, households in urban areas live in much better quality houses than those in rural areas. Household Assets: Households were asked if they owned farm implements, furniture and kitchenware, entertainment and communication equipment, personal items such as jewelry, as well as vehicles, tools and machineries. As expected, farm implements are common assets in rural areas while ownership of furniture and electronic items is more common among households in urban areas. Agriculture: The ESS agriculture modules cover crop farming and livestock rearing. The implementation closely follows the CSA s annual Agricultural Sample Survey (AgSS) with some modifications on content of the questionnaires and the scope of the survey. Agriculture (crop or livestock) is practiced approximately by 98 percent of the rural as well as 64 percent of the small town households. On average, a farm household has 11 fields. The average household land holding is 1.38 hectares which varies by place of residence and the gender of the household head. The most commonly used modern agricultural input is fertilizer. For the top five major cereal crops, the use of any types of fertilizers ranges from approximately 38 percent of sorghum to 83 percent of wheat grain fields. Improved seed is relatively common for maize (31 percent). Improved seed application in the remaining crops ranges from 2 to 8 percent of crop fields. Estimations based on self-report yield by field show that in 2015/16 meher season productivity for five major crops was as follows: maize 18 quintals per hectare; wheat 14 quintals per hectare; barley 10 quintals per hectare; sorghum 8 quintals per hectare; and teff 7 quintals per hectare. The crop disposition pattern of the five major crops shows that production is mainly for consumption (from percent). Sales account for 8 21 percent of crops produced. The composition varies by crop type. Farm households tend to sell more of high value crops such as teff and wheat and consume more of low value cereal crops such as sorghum and maize. Approximately 90 percent of rural households and 48 percent of small town area households are livestock holders. Cattle are the most important type of livestock owned by both rural and small town households and most are indigenous breeds. Modern input use in livestock other than immunization is limited. Non-Farm Enterprises: Non-farm enterprises (NFEs) are important in the lives of households and their number is increasing. Nationally, about 25 percent of households have one or more NFE. The three primary constraints to establishing NFEs include lack of financial services (35 percent), access to markets (30 percent), and transportation (14 percent). Other Income and Assistance: Cash and food transfers are the most common types of other incomes available to households. Approximately 19 percent of households received cash transfers from friends and relatives with an annual median amount of Birr 2,000 (approximately USD 90). Households also receive food, cash or
12 Executive Summary xi other nonfood in kind assistance from government and nongovernment programs. Time Use: The time use section collected information on time spent collecting fuelwood or water or working on agricultural activities, non-farm activities, temporary/casual work or salaried job. Household members were also asked about time spent on apprentice/unpaid type of activities. Time use patterns vary by gender and place of residence. Over half of female household members participate in water or fuelwood collection compared with less than a quarter of male household members. As expected, agricultural activities are more important in rural areas than in urban areas. Male household members are more likely to participate in agriculture activities than female members. Conversely, non-farm enterprise activities are more important in urban than rural areas. These activities are more likely to be carried out by female than male household members. Consumption, Expenditure, Food Security, Shocks and Coping: The survey included questions on expenditure on food and nonfood items, food security, shocks, and coping mechanisms. Cereals (rice, sorghum, barley, wheat) are the most important food items with over 90 percent of all households reporting consuming one of these items in any form in 6 of the last 7 days on average. The survey also finds that, when compared with rural households, small and large town households consume a more diverse diet. Clothing and shoes are the most important nonfood expenditure items. Households also spend substantial amount on laundry soap, kerosene, fuelwood, charcoal, transport, and taxes and levies. The average household level expenditure is higher in urban areas than in rural areas. Food availability is seasonal. Major planting seasons April to October are major slack months. Rural households tend to be the most affected by seasonal food shortage. Major shocks that affect households negatively are illness of a household member, drought, rise in the price of food items, and an increase in the price of inputs in order of importance. Households mainly deplete savings or sell livestock to cope with major shocks. Finance: Banking, Savings, Insurance and Credit: Approximately 22 percent of adults (18 years and older) have accounts from formal financial institutions. Financial inclusion at the household level is higher, at approximately 35 percent. Public commercial banks and microfinance institutions are the first and second most widely used institutions for financial services. Approximately 32 percent of individuals and 48 percent of households saved money in the past 12 months. Respondents also reported that they primarily saved in case of emergency. Regarding knowledge of financial procedures, approximately 45 percent of account owners know where to complain and 31 percent know what to do in the case that a financial service provider files for bankruptcy. Households take loans more frequently from informal sources (relatives, friends, neighbors) than formal sources. At the national level, the median household-level loan for a one-year period is 1000 Birr (45 USD).
13
14 Survey Objectives, Design and Implementation 1 Key Messages: The Ethiopia Socioeconomic Survey (ESS) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture program. ESS objectives include development of an innovative model for collecting agricultural data, inter-institutional collaboration, and comprehensive analysis of welfare indicators and socioeconomic characteristics. The survey is integrated with the CSA s Annual Agricultural Sample Survey (AgSS); the rural households included in the ESS are a sub-sample of the AgSS sample households. ESS is a panel survey. The first wave was implemented in , the second wave was carried out in and the third wave was implemented in The first wave covered only rural areas and small town areas. The second and third waves covered rural areas, small towns, and large towns. ESS uses a nationally representative sample of over 5,000 households living in rural and urban areas. The urban areas include both small and large towns. This report presents descriptive results from the third wave of data. 1.1 Objectives The Ethiopian Socioeconomic Survey (ESS) is a collaborative project between the Central Statistics Agency of Ethiopia (CSA) and the World Bank Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA) team. The objective of the LSMS-ISA is to collect multi-topic, household-level panel data with a special focus on improving agriculture statistics and generating a clearer understanding of the link between agriculture and other sectors of the economy. The project also aims to build capacity, share knowledge across countries, and improve survey methodologies and technology. The specific objectives of the ESS are: ll ll ll ll Develop an innovative model for collecting agricultural data in conjunction with household data; Strengthen the capacity to generate a sustainable system for producing accurate and timely information on households in Ethiopia; Develop a model of interinstitutional collaboration between the CSA and relevant federal and local government agencies as well as national and international research and development partners; and Generate comprehensive analysis of household income, well-being, and socioeconomic characteristics of households in Ethiopia.
15 2 Ethiopia Socioeconomic Survey The ESS contains several innovative features, including: ll ll ll ll ll ll ll Integration of household welfare data with agricultural data; Creation of a panel data set that can be used to study welfare dynamics, the role of agriculture in development, and the changes over time in health, education, and labor activities, inter alia; Collection of information on the network of buyers and sellers of goods with which the household interacts; Expanding the use of GPS units for measuring agricultural land areas; Involvement of multiple actors in government, academia, and the donor community in the development of the survey and its contents as well as its implementation and analysis; Implementation of a Computer Assisted Personal Interviewing (CAPI) application; Creation of publicly available micro datasets for researchers and policy makers. 1.2 Survey Design The ESS is designed to collect panel data in rural, small town, and urban areas on a range of household- and community-level characteristics linked to agricultural activities. The first wave was implemented in , the second wave was implemented in , and the third wave was implemented in The first wave, (originally referred to as ERSS, but since retitled ESS1), covered only rural and small town areas. 1 The second and the third waves, ESS2 and ESS3, respectively, added samples from large town areas. 2 ESS2 1 The ESS rural sample is integrated with the CSA s Annual Agricultural Sample Survey (AgSS). The ESS 290 rural Enumeration Areas are sub-samples of the AgSS. 2 The CSA defines small towns based on population estimates from the 2007 Population Census; a town with the population of less than 10,000 is categorized as a small town. Large towns include all other urban areas with the population of above 10,000. The small and large town classification used in this survey is due to the modification/expansion of the sample size from Wave 1 to Wave 2. and ESS3 are nationally representative. The planned follow-up ESS surveys will continue to be nationally representative. Table 1.1 presents the ESS sample by region and rural/ urban classification. The sample is a two-stage probability sample. The first stage of sampling entailed selecting primary sampling units, or CSA enumeration areas (EAs). A total of 433 EAs were selected based on probability proportional to size of the total EAs in each region. For the rural sample, 290 EAs were selected from the AgSS EAs. A total of 43 and 100 EAs were selected for small town and urban areas, respectively. In order to ensure sufficient sample size in the most populous regions (Amhara, Oromiya, SNNP, and Tigray) and Addis Ababa, quotas were set for the number of EAs in each region. The sample is not representative for each of the small regions including Afar, Benshangul Gumuz, Dire Dawa, Gambella, Harari, and Somalie regions. However, estimates can be produced for a combination of all smaller regions as one other region category. During the second wave 100 urban EAs were added. The addition also included one more region to the sample, Addis Ababa. In each EA 15 households were selected. The addition of urban EAs increased the sample size from 333 to 433 EAs and from 3,969 to 5,469 households. The second stage of sampling involved the selection of households from each EA. For rural EAs, a total of 12 households were sampled from each EA; of these, 10 households were randomly selected from the sample of 30 AgSS households. The AgSS households are those involved in farming or livestock activities. Another two households were randomly selected from all other nonagricultural households in the selected rural EA (those not involved in agriculture or livestock). In some EAs, there is only one or no such households, in which case, less than two nonagricultural households were surveyed and more agricultural households were interviewed instead so that the total number of households per EA remained the same.
16 Survey Objectives, Design and Implementation 3 Table 1.1 Ethiopia Socioeconomic Survey Sample Enumeration Areas Urban Total EAs Rural EAs Small Town EAs Large Town EAs National Regions Tigray Afar Amhara Oromiya Somali Benishangul-Gumuz SNNP Gambella Harari Dire Dawa Addis Ababa 20 NA NA 20 In the small town EAs, 12 households were selected randomly from the listing of each EA, with no stratification as to whether the household was engaged in agriculture/livestock activities. The same procedure was followed in large town EAs. However, 15 households were selected in each large town EA. Households were not selected using replacement. Thus, the final number of households interviewed was slightly less than the planned 5,469. In this wave (ESS3) 4,954 households were found and interviewed. 1.3 Instruments, Training and Fieldwork The survey comprised questionnaires at six different levels: household, water quality, community, post-planting agriculture, livestock, and post-harvest agriculture. The household questionnaire gathered information on basic demographics; education; health (including anthropometric measurement for children); labor and time use; partial food and nonfood expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; banking and savings; credit; and other sources of household income. The water quality questionnaire was added for ESS3. In addition to what was already included in the household module, this module includes further questions focusing on drinking water quality at the household and source level. This questionnaire also included microbial and chemical tests. The community questionnaire gathered information on access to infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information. Post-planting and post-harvest agriculture questionnaires were completed in those households where at least one member of the household engaged in crop farming on owned or rented land. The post-planting and post-harvest agriculture questionnaires focused on farming activities and solicited information on land ownership and use; farm labor; inputs use; GPS land
17 4 Ethiopia Socioeconomic Survey area measurement and coordinates of household fields; agriculture capital; irrigation; and crop harvest and utilization. The livestock questionnaire interviews were implemented in households where at least one member was engaged in livestock rearing. The livestock questionnaire collected information on animal holdings and costs, and production, cost and sales of livestock byproducts. Field staff training took place during July August 2015 and January February The July/August training sessions covered content training on the post-planting, livestock, and crop-cut questionnaires; the January/ February training focused on the post-harvest, household, and community questionnaires. Data collection began in September 2015 with the first of the two visits. The visits followed the AgSS fieldwork schedule. In the first visit enumerators conducted inventory of households using the household tracking questionnaire in rural areas and large and small town areas to locate panel households. They also conducted the post-planting and livestock interviews with those households who practiced agriculture (farming and/or livestock). The second visit took place in February April During the second visit, enumerators administered the household, community, and post-harvest agriculture questionnaires. 1.4 Data Entry and Cleaning The interviews were carried out using pen-and-paper (PAPI) as well as computer-assisted personal interviewing (CAPI) method. A concurrent data entry arrangement was implemented for PAPI. In this arrangement, the enumerators did not wait until all the interviews were completed. Rather, once the enumerators completed approximately 3 4 questionnaires, supervisors collected these interviews from enumerators and brought them to the branch offices for data entry. This process took place as enumerators continued administering interviews with other households. Then questionnaires were keyed at the branch offices as soon as they were completed using the CSPro data entry application software. The data from the completed questionnaires were then checked for any interview or data entry errors using a STATA program. Data entry errors were flagged for the data entry clerks and the interview errors were then sent to back to the field for correction and feedback to the ongoing interviews. Several rounds of this process were undertaken until the final data files were produced. Additional cleaning was carried out, as needed, by checking the hard copies. In ESS3, CAPI (with a Survey Solutions platform) was used to collect the community data in large town areas. More detailed information on the instruments, modifications and new additions, as well as fieldwork issues, is provided in the survey s Basic Information Document (BID). The BID, this Basic Report, questionnaires, and manuals are available online along with the data. 1.5 Organization of the Survey Report This survey report is a statistical abstract that pre - sents a description of various socioeconomic variables covered in the survey. The results presented have been weighted to be nationally representative for rural areas, small towns, and large towns. For regional estimates, results are presented for five regions and the remaining six regions (Afar, Benshangul-Gumuz, Dire Dawa, Gambella, Harari and Somali regions) are grouped into an other region category. The values reported for the other region category should be interpreted with caution as they reflect averages for these six regions. These regions are different in their levels of development. As a result, the combined average obtained for this category may not be intuitive for some regions in the group. The rest of the report is organized as follows: Chapter 2 presents demographic information as well as education
18 Survey Objectives, Design and Implementation 5 and health outcomes. Chapter 3 presents information on housing characteristics and household assets. Chapter 4 presents information on agriculture activities, and Chapter 5 includes information on nonfarm economic activities. Chapter 6 covers time use and labor. Chapter 7 focuses on consumption, food security and shocks. Chapter 8 summarizes data on financial inclusion. There is a separate report for results from the Water Quality Survey.
19
20 Demography, Education and Health 2 Key Messages: Average household size is 5.2 persons in rural, 4.3 persons in small town and 3.7 persons in large town areas. Dependency ratio is higher in rural areas (100 percent) than in small town (69 percent) and large town areas (48 percent). Self-reported literacy (for reading and writing in any language) is 59 percent for males and 43 percent for females. Gender inequality in literacy is observed in all age groups and all regions. About 30 percent of boys and girls aged 7 18 years are not in school. Approximately 65 percent are enrolled in primary schools and the remaining 6 percent are enrolled in secondary schools. Prevalence of self-reported illness for the 4 weeks preceding the survey is 9 percent for males and 12 percent for females. Disability, defined as having difficulty hearing, seeing, walking or climbing, remembering or concentrating, self-care including washing, dressing and feeding, and communicating or understanding, is higher for the oldest group (aged 51 and above), with females exhibiting more disabilities than males in that age group. Overall health care utilization for treatment or checkups (measured over the 4 weeks preceding the survey) is approximately 8 percent for males and 11 percent for females. Frequently cited reasons for not seeking consultation include distance, affordability, and the fact that individuals do not normally go to health facilities for a regular health checkup. Under-5 stunting, underweight and wasting prevalence falls at 42, 24, and 10 percent respectively. 2.1 Household Demography Average Household Size, Age Distribution, and Dependency Ratio Table 2.1 presents information about household size, dependency ratio, and age distribution by place of residence. The average household size in Ethiopia is 4.8 persons. Average household size is higher in rural areas (5.2 persons per household) than in small towns (4.3 persons) and large towns (3.7 persons). Regional differences are also observed; SNNP and Oromiya have the highest average household size with 5.2 persons per household. The combined average for the other regions category is 5 persons per household. Amhara and Addis Ababa have the smallest average household size, at 4.2 persons/household. Although there are some differences by place of residence, the age distribution, in general, shows that the Ethiopian population is young. Those who are under 15 years old account for more than 43 percent of the total population. Persons aged 65 and above account for only 4 percent of the total population. The working age population (15 64 years) makes up 52 percent of the population.
21 8 Ethiopia Socioeconomic Survey Table 2.1 Demographic Characteristics Average Household Size, Dependency Ratio and Age Group by Place of Residence, Ethiopia 2016 Percentage of Population by Age Group Average HH Size Dependency Ratio Tigray Amhara Oromiya SNNP Addis Ababa Other regions Rural Small town (urban) Large town (urban) Country The dependency ratio in rural areas is much higher than that of small and large town areas (100 percent, versus 69 and 48 percent respectively).3 Most of the dependents in rural areas come from the lower end of the age distribution, likely driven by higher fertility in rural areas. By region, dependency ratio ranges from 42 percent in Addis Ababa city administration to 97 percent in Oromiya and SNNP regions Religious Affiliation Table 2.2 shows religious affiliations of household members aged 10 years and above. Approximately half of the respondents are Orthodox Christians. Muslims and Protestants comprise 26 and 22 percent of respondents, respectively. Orthodox Christians are the majority in Tigray and Amhara with 96 and 82 percent, respectively; 73 percent of the population is Muslim in the Other regions category (Afar, Benshangul Gumuz, Dire Dwawa, Harari, Gambella and Somali regions combined). Muslims are also the majority in Oromiya (40 percent). Protestant followers are the largest in the SNNP region, with 64 percent of the population Marital Status Table 2.3 summarizes the marital statuses of respondents aged 10 years and above. More than 47 percent have never been married and 42 percent are in a monogamous marriage. Five percent of respondents are widowed, while divorced and separated persons account for 4 percent of the relevant population. 4 Polygamous marriages are rare (less than 1 percent). The proportion of those who have never been married is the highest in Addis Ababa (53 percent) and is the lowest in Amhara region (42 percent). 3 Total dependency ratio is defined as population that is not of working age (<15 and >64) divided by total number of working age persons (15 64 years). The value is then multiplied to express it in percent. Households with no working persons were excluded in the dependency ratio computation. A dependency ratio that is above 100 means that there is, on average, more than one dependent (young or elderly person) in the household for each prime-age adult member to support Parental Characteristics: Education and Occupation For all household members less than 18 years, information was collected on the education and occupation statuses of biological parents (Table 2.4 Panel A and B). 4 Age 10 years and above.
22 Demography, Education and Health 9 Table 2.2 Religious Affiliation Percent of Population, by Region and Place of Residence (Ages 10+), Ethiopia 2016 Percent of Population by Religion Orthodox Catholic Protestant Muslim Waqifata Other Tigray Amhara Oromiya SNNP Addis Ababa Other regions Rural Small town (urban) Large town (urban) Country Table 2.3 Marital Status Percent of Population by Region and Place of Residence (Ages 10+), Ethiopia 2016 Percent of Population by Marital Status Never Married Married (monogamous) Married (polygamous) Divorced Separated Widowed Tigray Amhara Oromiya SNNP Addis Ababa Other regions Rural Small town (urban) Large town (urban) Country For the majority respondents less than 18 years, both biological parents either do not have any education or have only some primary level education. Mothers educational attainment is much lower than that of fathers. Approximately 60 percent of fathers have completed at least primary school, while only 33 percent of mothers did the same. In both cases, most of this educational attainment is limited to primary level. As expected, education levels are higher for parents in large towns as compared with small towns and rural areas. Agriculture is the main occupation for both the fathers and mothers in rural areas with 97 and 50 percent, respectively, engaging in this activity. It is also the most important occupation for small town residents. However, parental occupations in large towns are more diverse. Other occupational sectors, such as trade, education, professional/scientific, manufacturing and construction are more common in both large and small towns.
23 10 Ethiopia Socioeconomic Survey Table 2.4 Education and Occupation of Biological Parents Percent of Education and Occupation of Fathers and Mothers of Children (<18 years), Ethiopia 2016 Place of Residence Country Rural Small Town (urban) Large Town (urban) Father Mother Father Mother Father Mother Father Mother Panel A: Education level No education Primary Secondary Above secondary Panel B: Occupation Agriculture Mining Manufacturing Professional/scientific Electricity Construction Transportation Buying and selling Financial services Personal services Education Health Public administration Household chores, housewife Other Education Literacy Information on literacy, the ability to read and write in any language, was collected for all household members 5 years and older (Table 2.5). The respondents were not tested for their ability to read or write. Therefore, the percentages presented in Table 2.5 are based on self-reported ability to read and write. There is substantial gender inequality in literacy across age groups and regions. At the national level, more than half (64 percent) of males are literate, compared to 48 percent of females. The oldest (30+ years old) cohorts tend to be less literate than younger age groups. This might be due to a recent expansion in primary and secondary education, an opportunity that was not available for the oldest cohort (30+ years old). By region, literacy rates are highest for both males and females in Addis Ababa (97 and 87 percent, respectively); literacy is lowest in the Other regions category. In all other major regions, literacy rates range from 44 percent for females in Amhara to 71 percent for males in Tigray. By place of residence, as expected, literacy is the highest in large towns followed by small towns and rural areas.
24 Demography, Education and Health 11 Table 2.5 Literacy Percent of Literate Individual, by Age Group, Place of Residence, and Region Males Age Group Females Age Group All All Tigray Amhara Oromiya SNNP Addis Ababa 96.7 (90.8) (100.0) (100.0) (100.0) (79.2) (92.4) (98.0) Other regions Rural Small town (urban) Large town (urban) Country Note: Values in parentheses are based on less than 100 observations Enrollment Enrollment for school age population (ages 7 18 years) is shown in Table 2.6. Overall enrollment for boys and girls in primary and secondary schools is approximately 70 percent. The majority of this enrollment is at the primary level; the contribution of secondary enrollment to the total enrollment is about five percent. Interestingly, female and male enrollment levels are comparable in both primary and secondary school School Types and Proximity Almost all pupils who are currently attending school go to government schools (Table 2.7). However, non-government schools are important in large towns; the proportion of the school-age population attending non-government schools in large towns is approximately 28 percent. By region, the share of 5 The figures in Table 2.6 are not enrollment rates. The percentages indicate values from the total school age population and shows where children in that age cohort are now by education level. nongovernment schools is the highest in Addis Ababa (46 percent). In the rest of the regions, the share of nongovernmental schools ranges from less than 2 percent in Amhara to 9 percent among the Other regions category. Proximity to school for students currently attending school is measured in minutes, regardless of the mode of transportation used to go to the school (Table 2.7). At the country level, approximately 79 percent of students reach their nearest primary school in less than 30 minutes. Similarly, 71 percent of the students attending secondary school get to school within the same amount of time. Also, as expected, school children in urban areas are closer to both primary and secondary schools. Approximately 61 percent of large town area students and 69 percent of small town area students get to their primary school within 15 minutes, while only 36 percent of students in rural areas reach their primary school in this same amount of time. A similar profile is observed for secondary school proximity.
25 12 Ethiopia Socioeconomic Survey Table 2.6 Enrollment School Enrollment by Gender, Level, Region and Place of Residence (ages 7 18), Ethiopia 2015/16 Males (%) Females (%) Not Enrolled Primary Secondary Not Enrolled Primary Secondary Tigray Amhara Oromiya SNNP Addis Ababa (11.6) (61.5) (26.9) Other regions Rural Small town (urban) Large town (urban) Country Note: Values in parentheses are based on less than 100 observations. Table 2.7 School Types and Travel Time to School Percent among Enrolled Students (Ages 7 18), by Place of Residence Ethiopia 2015/16 School Type Travel Time (minutes) Primary School Secondary School Gov t Nongov t Tigray (53.9) (29.8) (9.7) (6.6) Amhara Oromiya SNNP Addis Ababa (49.6) (34.1) (16.3) (0.0) Other regions (49.4) (33.3) (15.7) (1.5) Rural Small town (urban) (53.4) (33.1) (10.8) (2.6) Large town (urban) Country Note: Values in parentheses are based on less than 100 observations Reasons for Absenteeism Students were asked if they missed classes for more than a week during the month preceding the survey (approximately some time between January and March 2016). Approximately 13 percent of those enrolled in school missed classes for more than a week. Table 2.8 summarizes reasons for absenteeism. Death or illness in the family was the most commonly cited reason (60 percent), followed by work (30 percent). Eleven percent of the respondents mentioned other reasons School Expenses School expenses for the academic year preceding the survey are shown in Table 2.9. Approximately 52 percent of those in primary schools pay less than 100 Birr on average. Secondary schools require higher school
26 Demography, Education and Health 13 Table 2.8 Reasons for Absenteeism Percent among Enrolled Students (Ages 7 18) by Gender, Region and Place of Residence, Ethiopia 2015/16 Reason for Being Absent % of Enrolled Students Absent Work Illness or Death in the Family Other Tigray 6.8 (25.0) (70.6) (4.4) Amhara 14.3 (17.2) (72.8) (10.0) Oromiya 18.9 (28.5) (55.3) (16.2) SNNP 4.3 (63.4) (35.9) (0.7) Addis Ababa 2.2 (67.4) (0.0) (32.6) Other regions 4.8 (61.5) (37.9) (0.6) Rural Small town (urban) 9.8 (41.9) (55.3) (2.8) Large town (urban) 3.3 (66.0) (27.1) (7.0) Country Note: Values in parentheses are based on less than 100 observations. Table 2.9 School Expenses Percent among Enrolled Students (Ages 7 18) by Level of Education, Region and Place of Residence, Ethiopia 2015/16 School Expenses (Birr) Primary School Secondary School < < Tigray (2.1) (4.2) (3.7) (66.6) (23.4) Amhara Oromiya SNNP Addis Ababa (0.0) (0.0) (0.0) (12.5) (87.5) Other regions (4.1) (7.8) (5.4) (58.9) (23.8) Rural Small town (urban) (3.2) (1.8) (2.3) (60.4) (32.3) Large town (urban) Country Note: Values in parentheses are based on less than 100 observations. expenses; 90 percent paid more than 150 Birr a year. The level of school fees increases with urban density: primary school fees are higher in Addis Ababa than anywhere else in the country. This could be due to the higher share on nongovernment/private schools in Addis Ababa than in all other regions. 2.3 Health Prevalence of illness Table 2.10 presents information on self-reported health problems in the 4 weeks preceding the survey. At the national level, self-reported prevalence of
27 14 Ethiopia Socioeconomic Survey Table 2.10 Health Problems in the Past 4 Weeks Percent of Population Reporting Any Self-Reported Health Problems in the Past 4 Weeks by Gender, Age Group, Region and Place of Residence, Ethiopia 2016 Males Age Group Females Age Group All All Tigray (16.4) Amhara Oromia SNNP Addis Ababa 13.7 (18.7) (9.7) 11.3 (37.5) 12.9 (10.8) (5.8) 13.8 (22.6) Other regions Rural Small town (urban) (4.5) (32.7) Large town (urban) Country Note: Values in parentheses are based on less than 100 observations. illness is slightly higher for females (12 percent) than males (9 percent). Prevalence of illness also differs by region. For females, health problems are least prevalent in SNNP and most prevalent in other regions ; for males, prevalence is lowest in SNNP and highest in Addis Ababa. There are also considerable age-group differences. For males and females, the proportion of those in the oldest age group (60 years and older) with health problems is more than twice the average seen in all other age groups Disability Information on health difficulties is collected from all members of the household ages 5 and older. These questions pertain to disabilities in six areas: hearing, seeing, walking or climbing, remembering or concentrating, self-care (washing, dressing and feeding), and communicating or understanding. Table 2.11 summarizes disability prevalence for three different age groups. Approximately 1 percent of male and females in the youngest age group have some disability (Table 2.11 Panel A). Prevalence is similar for the next age group (18 50 years old) (Table 2.11 Panel B). However, health disabilities appear to be more common among the oldest age group (51 years old and above) (Table 2.11 Panel C) Consultation for Health and Type of Facility Visited All respondents were asked if they went to a modern health facility or a traditional place for treatment or checkup during the past 4 weeks regardless of illness. Table 2.12 presents the results. Overall, approximately 8 and 12 percent of males and females, respectively, sought a health consultation in the past 4 weeks. At the national level, the majority of those who reported visiting health facilities or traditional places fell mostly within the 60 and above age group. By region, health facility utilization is the highest in Tigray and Addis Ababa for males and in Tigray and other regions for females. Table 2.13 summarizes the type of health facility visited, among individuals who reported visiting at least one facility in the past 4 weeks. At the national level, the majority of individuals sought services at health centers (40 percent), followed by clinics (21 percent)
28 Demography, Education and Health 15 Table 2.11 Health Difficulties/Disabilities Percent of the Population with Any Health Difficulties/Disabilities by Type, Gender, Age, Region and by and Place of Residence, Ethiopia 2016 Health Difficulty/Disability Hearing Seeing Walking/ Climbing Remembering/ Communicating Self-Care Communicating/ Understanding Male Female Male Female Male Female Male Female Male Female Male Female PANEL A: AGED 5 17 Tigray Amhara Oromia SNNP Addis Ababa (1.9) 0.7 (5.4) 4.5 (1.9) 0.7 (3.8) 0.7 (1.9) 0.7 (3.8) 0.7 Other regions Rural Small town (urban) Large town (urban) Country PANEL B: AGED Tigray Amhara Oromia SNNP Addis Ababa Other regions Rural Small town (urban) Large town (urban) Country PANEL C: AGED 51+ Tigray Amhara Oromia SNNP Addis Ababa (6.2) (7.5) (29.4) (34.7) (12.3) (24.2) (4.3) (9.5) (1.4) (1.8) (0.0) (2.5) Other regions Rural Small town (urban) (8.5) (19.0) (26.8) (43.9) (9.7) (28.7) (3.8) (14.2) (5.2) (4.9) (0.0) (1.9) Large town (urban) Country Note: Values in parentheses are based on less than 100 observations.
Ethiopia - Socioeconomic Survey
Microdata Library Ethiopia - Socioeconomic Survey 2013-2014 Central Statistics Agency of Ethiopia (CSA) - Ministry of Finance and Economic Development, Living Standards Measurement Study Integrated Surveys
More informationEthiopia - Socioeconomic Survey , Wave 3
Microdata Library Ethiopia - Socioeconomic Survey 2015-2016, Wave 3 Central Statistical Agency of Ethiopia - CSA Report generated on: April 2, 2018 Visit our data catalog at: http://microdata.worldbank.org
More informationEthiopia - Rural Socioeconomic Survey
Microdata Library - Rural Socioeconomic Survey 2011-2012 Central Statistical Agency - Ministry of Finance and Economic Development, Living Standards Measurement Study Team - The World Bank Report generated
More informationLSMS-Integrated Surveys on Agriculture General Household Survey Panel
LSMS-Integrated Surveys on Agriculture General Household Survey Panel 2015/2016 A Report by the Nigerian National Bureau of Statistics in Collaboration with the Federal Ministry of Agriculture and Rural
More informationRole of agricultural cooperatives and storage in rural Ethiopia: Results of two surveys
Role of agricultural cooperatives and storage in rural Ethiopia: Results of two surveys September 2012 Nicholas Minot Daniel Ayalew Mekonnen International Food Policy Research Institute Washington, DC
More informationCHAPTER III SOCIO-ECONOMIC CHARACTERISTICS OF THE POPULATION IN AGRICULTURAL HOUSEHOLDS
CHAPTER III SOCIO-ECONOMIC CHARACTERISTICS OF THE POPULATION IN AGRICULTURAL HOUSEHOLDS 1 INTRODUCTION Population as a producer and consumer is closely related with agriculture. On the one hand, population
More informationSamia Zekaria Member and Secretary, Population Census Commission
FOREWORD Statistical data that reflect the socio-economic and demographic conditions of the residents of a country are useful for designing and preparation of development plans as well as for monitoring
More informationAGRICULTURAL SAMPLE SURVERY 2005/06( 1998 E.C) VOLUME V
THE FEDERAL DEMOCRATIC REPUBLIC OF ETHIOPIA CENTRAL STATISTICAL AGENCY AGRICULTURAL SAMPLE SURVERY 2005/06( 1998 E.C) VOLUME V REPORT ON AREA AND PRODUCTION OF BELG SEASON CROPS FOR PRIVATE PEASANT HOLDINGS
More informationThe office hopes that the data contained in this part of the Statistical Report will be utilized by all data users for various development planning.
FOREWORD Statistical data that reflect the socio-economic and demographic conditions of the residents of a country are useful for designing and preparation of development plans as well as for monitoring
More informationCash transfers and productive impacts: Evidence, gaps and potential
Cash transfers and productive impacts: Evidence, gaps and potential Benjamin Davis Strategic Programme Leader, Rural Poverty Reduction Food and Agriculture Organization Transfer Project Workshop Addis
More informationCHAPTER VI FARM MANAGEMENT PRACTICES 1. INTRODUCTION
CHAPTER VI FARM MANAGEMENT PRACTICES 1. INTRODUCTION Agriculture and allied activities have been described as the main sources of much of the raw materials, investment capital, foreign exchange and labor
More informationVULNERABILITY ANALYSIS AND MAPPING (VAM), WORLD FOOD
The nominal retail prices of food commodities across district markets were stable and further decreased in some markets where the belg crop production shows good performance and root crops are being consumed.
More informationThe productive impact of cash transfers in Sub-Saharan Africa
The productive impact of cash transfers in Sub-Saharan Africa Benjamin Davis Strategic Programme Leader, Rural Poverty Reduction Food and Agriculture Organization Designing and implementing high-quality,
More informationAssessing Poverty in Kenya
Findings reports on ongoing operational, economic and sector work carried out by the World Bank and its member governments in the Africa Region. It is published periodically by the Africa Technical Department
More informationCHAPTER 4 LIST OF ITEMS FOR THE CENSUS OF AGRICULTURE
29 CHAPTER 4 LIST OF ITEMS FOR THE CENSUS OF AGRICULTURE This chapter contains recommended items for inclusion in the census of agriculture according to their suitability for the core and supplementary
More informationGender in the Lao PDR on the agriculture sector
Gender in the Lao PDR on the agriculture sector By: Mr. porha SAYCHOUNORSOUA Staff of the Center for Statistics and Information (CSI), Department of Planning and Cooperation, MAF and Ms Samta Sacktikun
More informationDynamics of Poverty and Wellbeing in Ethiopia
Dynamics of Poverty and Wellbeing in Ethiopia An Introduction to a Special Issue of the Ethiopian Journal of Economics 1 Dean Jolliffe 2, Alemayehu Ambel 1, Tadele Ferede 3 and Ilana Seff 4 Abstract Understanding
More informationFrom Protection to Production: measuring the impact of social cash transfers on local economic development in Africa
From Protection to Production: measuring the impact of social cash transfers on local economic development in Africa Benjamin Davis FAO, PtoP and Transfer Project Scoping Conference The Links between Social
More information2016 Post-Distribution Assessment Results
2016 Post-Distribution Assessment Results FAO s Meher season emergency seed response to the El Niño-induced drought in Ethiopia 1 Food and Agriculture Organization of the United Nations Ethiopia Country
More informationEl Niño in Ethiopia. Analyzing the summer kiremt rains in 2015
Agriculture Knowledge, Learning Documentation and Policy (AKLDP) Project, Ethiopia Technical Brief December 2015 El Niño in Ethiopia Introduction In September 2015 an AKLDP Technical Brief El Niño in Ethiopia,
More informationMain Findings. Key Definitions RWANDA FOOD AND NUTRITION SECURITY MONITORING SYSTEM (FNSMS)
RWANDA M I N A G R I I n s i d e t h i s i s s u e : Main Findings 1 Key Definitions 1 Food security situation aligned to seasonal patterns Chronic malnutrition remains high among children under 5 Poor
More informationThe impact of social cash transfers on labour market outcomes: the evidence from sub-saharan Africa
The impact of social cash transfers on labour market outcomes: the evidence from sub-saharan Africa Benjamin Davis Food and Agriculture Organization, the From Protection to Production Project, and the
More informationPOVERTY PROFILE OF ETHIOPIA: Analysis based on the 1999/00 HICE & WM Survey Results
POVERTY PROFILE OF ETHIOPIA: Analysis based on the 1999/00 HICE & WM Survey Results Welfare Monitoring Unit (WMU) Ministry of Finance and Economic Development (MOFED) Federal Democratic Republic of Ethiopia
More informationTanzania National Panel Survey LSMS-ISA: Gender
EPAR Brief No. 190 March 30, 2012 Tanzania National Panel Survey Living Standards Measurement Study - Integrated Surveys on Agriculture gender Professor Leigh Anderson, Principal Investigator Associate
More informationAnnex 1: Productivity of Non-farm Enterprises
Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Annexes Annex 1: Productivity of Non-farm Enterprises 1. Labor productivity is defined
More informationMARKET ANALYSIS NOTE #4
MARKET ANALYSIS NOTE #4 Grain Market Research Project Ministry of Economic Development and Cooperation March 997 Meeting Food Aid and Price Support Objectives Through Local Grain Purchase: A Review of
More informationCereal Marketing and Household Market Participation in Ethiopia: The Case of Teff, Wheat and Rice
AAAE Conference Proceedings (2007) 243-252 Cereal Marketing and Household Market Participation in Ethiopia: The Case of Teff, Wheat and Rice Berhanu Gebremedhin 1 and Dirk Hoekstra International Livestock
More informationETHIOPIA MONTHLY MARKET WATCH
- 214 Highlights The general year to year inflation which is based on comparison of current and last year similar month Consumer Price Index, stood at 6.2% for ember 214. The food part of the inflation
More informationClimate change impact on Ethiopian small holders production efficiency
Fifth IAERE Annual Conference 16 17 February 2017, Rome Climate change impact on Ethiopian small holders production efficiency Solomon Asfaw, FAO, Agricultural Development Economics Division (ESA) Sabrina
More informationResults from impact evaluation of cash transfer programs in sub-saharan Africa
Results from impact evaluation of cash transfer programs in sub-saharan Africa Benjamin Davis FAO, PtoP and Transfer Project Conferencia Nacional de Assistencia Social Monday, October 21, 2013 Luanda,
More informationLivestock and livelihoods spotlight ETHIOPIA
Livestock and livelihoods spotlight ETHIOPIA Cattle sector Financial support provided by the United States Agency for International Development (USAID) Cattle and livelihoods spotlight Ethiopia Introduction
More informationLivelihood Profile Oromiya Region, Ethiopia
Livelihood Profile Oromiya Region, Ethiopia 1 April 2008 Zone Description The Bale Agro-pastoral livelihood zone is located Goro, Ginir, Sawena, Legahida, Berbere, Guradamole and Meda- Aelabu woredas of
More informationTHE FEDERAL DEMOCRATIC REPUBLIC OF ETHIOPIA CENTRAL STATISTICAL AGENCY AGRICULTURAL SAMPLE SURVEY 2006 / 2007 (1999 E.C.) (September December, 2006)
THE FEDERAL DEMOCRATIC REPUBLIC OF ETHIOPIA CENTRAL STATISTICAL AGENCY AGRICULTURAL SAMPLE SURVEY 2006 / 2007 (1999 E.C.) (September December, 2006) VOLUME IV REPORT ON LAND UTILIZATION (PRIVATE PEASANT
More informationVIABILITY OF AGRICULTURAL INPUT VOUCHERS
Assessment Report VIABILITY OF AGRICULTURAL INPUT VOUCHERS in Grey Zone Areas of Donetsk and Luhansk Regions of Eastern Ukraine People in Need (PIN) October 2016 CONTENTS EXECUTIVE SUMMARY... 3 INTRODUCTION...
More informationFOOD SECURITY MONITORING, TAJIKISTAN
Fighting Hunger Worldwide BULLETIN July 2017 ISSUE 19 Tajikistan Food Security Monitoring FOOD SECURITY MONITORING, TAJIKISTAN July 2017 - ISSUE 19 Fighting Hunger Worldwide BULLETIN July 2017 ISSUE 19
More informationETHIOPIA MONTHLY MARKET WATCH
ETHIOPIA MONTHLY MARKET Highlights Compared to 2013, country level general inflation rate increased by 9.1%; food inflation by 8% and non-food by 10.3%. Of the food index components, higher increase in
More informationGENDER BASED DIFFERENCES AMONG ENTREPRENEURS AND WORKERS IN LEBANON
GENDER BASED DIFFERENCES AMONG ENTREPRENEURS AND WORKERS IN LEBANON A GENDER FOCUSED ANALYSIS DRAWING FROM THE LEBANON INVESTMENT CLIMATE ASSESSMENT (ICA) Presentation Outline 2 Key points: Purpose of
More informationCensus of Economic Establishments in Ethiopia
Census of Economic Establishments in Ethiopia 1. Introduction In general, it is obvious that, availability of relevant, reliable and up to date statistical data is considered indispensable for the evaluation
More informationTHE ECONOMIC CASE FOR THE EXPANSION OF SOCIAL PROTECTION PROGRAMMES
THE ECONOMIC CASE FOR THE EXPANSION OF SOCIAL PROTECTION PROGRAMMES FAO/Ivan Grifi KEY MESSAGES n Cash transfer programmes generate a broad range of social and economic impacts, including enhancing the
More informationETHIOPIA MONTHLY MARKET WATCH
ETHIOPIA MONTHLY MARKET Highlights The country level general inflation and food inflation rate increased by 39.2% and 50.3% respectively as compared to 2010. However, month to month general and food inflation
More informationETHIOPIA MONTHLY MARKET WATCH
ETHIOPIA MONTHLY MARKET Highlights The country level general and food inflation rate increased by 40.6% and 49.9% respectively compared to 2010. Cereal inflation rate increased by 52.3%. The Ethiopian
More informationTHE FEDERAL DEMOCRATIC REPUBLIC OF ETHIOPIA CENTRAL STATISTICAL AGENCY AGRICULTURAL SAMPLE SURVEY 2011/2012 (2004 E.C.) (September December, 2011)
THE FEDERAL DEMOCRATIC REPUBLIC OF ETHIOPIA CENTRAL STATISTICAL AGENCY AGRICULTURAL SAMPLE SURVEY 2011/2012 (2004 E.C.) (September December, 2011) VOLUME IV REPORT ON LAND UTILIZATION (PRIVATE PEASANT
More informationFourth High Level Forum on United Nations Global Geospatial Information Management (UN-GGIM) Key Note Ministerial Statement By Yinager Dessie Belay
Fourth High Level Forum on United Nations Global Geospatial Information Management (UN-GGIM) Key Note Ministerial Statement By Yinager Dessie Belay (PhD) With the Rank of Minister, Commissioner of National
More informationETHIOPIA Food Security Update November 2007
Pastoral and agropastoral populations in southern Somali Region remain extremely food insecure as a result of poor deyr rains and ongoing restrictions on trade and movement in Warder, Degahabour, Korahe
More informationThe office hopes that the data contained in this Statistical Report will be utilized by all data users for various development planning.
FOREWORD Statistical data that reflect the socio-economic and demographic conditions of the residents of a country are useful for designing and preparation of development plans as well as for monitoring
More informationCodebook for the Cross-National Equivalent File
Codebook for the Cross-National Equivalent File 1998-2014 BHPS HILDA KLIPS PSID RLMS-HSE SHP SLID SOEP KLIPS Data File 1998-2014 Prepared by: KLIPS Team Korea Labor Institute Variables in the KLIPS Cross-National
More informationPERCEPTION OF FARMERS TOWARDS RURAL CHILDREN S FORMAL EDUCATION IN OSUN STATE, NIGERIA
111 PERCEPTION OF FARMERS TOWARDS RURAL CHILDREN S FORMAL EDUCATION IN OSUN STATE, NIGERIA Ayoade Adenike Rebecca* *Department of Agricultural Extension and Rural Development, Faculty of Agricultural Sciences,
More informationImpact of Social Protection and Agriculture: Child Grants Programme (CGP) and complementary support
Impact of Social Protection and Agriculture: Child Grants Programme (CGP) and complementary support Silvio Daidone From Protection to Production (PtoP) Workshop on Social Protection and Agriculture in
More information65,000 peoples income increased. 350,000 financial accounts created. 48,000 jobs created. 300 Million invested. Poverty reduction.
ENTERPRISE PARTNERS is a social enterprise funded by DfID. Established to facilitate agro-industrial growth and enable access to finance in Ethiopia. This will result in job and income opportunities for
More informationThe role of livestock in poverty reduction Challenges in collecting livestock data in the context of living standard household surveys in Africa
The role of livestock in poverty reduction Challenges in collecting livestock data in the context of living standard household surveys in Africa Alberto Zezza Development Research Group The World Bank
More informationNonfarm Enterprises in Rural Ethiopia: Improving Livelihoods by Generating Income and Smoothing Consumption?
Nonfarm Enterprises in Rural Ethiopia: Improving Livelihoods by Generating Income and Smoothing Consumption? Julia Kowalski 1, Alina Lipcan 2, Katie McIntosh 2, Remy Smida 3, Signe Jung Sørensen 4, Ilana
More informationAnnual Agricultural Surveys
REPUBLIC OF NAMIBIA Report on the Annual Agricultural Surveys 1996-2003 BASIC ANALYSIS OF COMMUNAL AGRICULTURE Central Bureau of Statistics National Planning Commission Private Bag 13356 WINDHOEK NOVEMBER,
More informationCentral Statistical Agency National Integrated Household Survey Agricultural Sample Survey, 2009/2010 (2002 E.C)
QUESTIONNAIRE 1 Central Statistical Agency National Integrated Household Survey Agricultural Sample Survey, 2009/2010 (2002 E.C) Ag.S.S. Form 2002/0 Part I - Identification Particulars 1 2 3 4 5 Region
More informationLabour Force Growth and its Effects on Ethiopian Rural Economy: A Study of Growth Policy Options. Tsegaye Tegenu (Ph.D.)
Labour Force Growth and its Effects on Ethiopian Rural Economy: A Study of Growth Policy Options Tsegaye Tegenu (Ph.D.) Institute for Futures Studies, and Stockholm University Introduction This piece is
More informationFrom Protection to Production. An overview of impact evaluations on Social Cash Transfers in Sub Saharan Africa
From Protection to Production. An overview of impact evaluations on Social Cash Transfers in Sub Saharan Africa Benjamin Davis FAO, PtoP and the Transfer Project Expert Discussion GIZ Eschborn July 11,
More informationDeterminants of Smallholder Food Consumption Commercialization. in Ethiopia
Available online at: http://euroasiapub.org, pp. 55~66 Thomson Reuters Researcher ID: L-5236-2015 Determinants of Smallholder Food Consumption Commercialization in Ethiopia Abraha Gebru Tedla Abraha Gebru
More informationSTAPLE FOOD CROPS TURNING INTO COMMERCIAL CROPS: CASE STUDIES OF TEFF, WHEAT AND RICE IN ETHIOPIA 1
STAPLE FOOD CROPS TURNING INTO COMMERCIAL CROPS: CASE STUDIES OF TEFF, WHEAT AND RICE IN ETHIOPIA 1 Berhanu Gebremedhin 2 and Dirk Hoekstra Abstract Teff, wheat and rice are becoming important market oriented
More informationLABOUR FORCE QUESTIONNAIRE 2
LABOUR FORCE QUESTIONNAIRE The questionnaire is filled in for the household members aged 15-75 (including). The questionnaire isn t filled in for the household members aged 15-75 (including) years, who
More informationETHIOPIA AGRICULTURAL SNAPSHOT 2011/12
ETHIOPIA AGRICULTURAL SNAPSHOT 2011/12 Roberts, Cleophelia; Azzarri, Carlo MARCH, 2014 HARVESTCHOICE - INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE (IFPRI) harvestchoice.org Abstract The purpose of this
More informationEast African PLEC General Meeting Arusha, Tanzania, 26-28, November, Household Diversity in the Smallholder farms of Nduuri, Embu, Kenya.
Household Diversity in the Smallholder farms of Nduuri, Embu, Kenya. Mugo C.R, B.O. Okoba, E.H. Ngoroi, and, J. N. Kang ara Abstract. Interviews were carried out for Nduuri farmer communities to establish
More informationFARM MANAGEMENT PRACTICES
THE FEDERAL DEMOCRATIC REPUBLIC OF ETHIOPIA CENTRAL STATISTICAL AGENCY AGRICULTURAL SAMPLE SURVEY 2007 / 2008 (2000 E.C.) (September December, 2007) VOLUME III REPORT ON FARM MANAGEMENT PRACTICES (PRIVATE
More informationThe present study has certain specific research objectives: 1. ' To study the distribution and growth of landless labourers in the study area.
The role which the landless labourers play in the agricultural economy is very crucial and important because the availability of labour is a major constraint in the agricultural land use and cropping patterns
More informationLivelihood Diversification in. Communities of Ethiopia- Prospects and Challenges. Kejela Gemtessa, Bezabih Emana Waktole Tiki WABEKBON Consult
Livelihood Diversification in Borana Pastoral Communities of Ethiopia- Prospects and Challenges Kejela Gemtessa, Bezabih Emana Waktole Tiki WABEKBON Consult The Paper was part of the study on participatory
More informationZimbabwe Household Livelihood Security Assessment. Catholic Relief Services.
DePaul University From the SelectedWorks of John Mazzeo, Ph.D. 2009 Zimbabwe Household Livelihood Security Assessment. Catholic Relief Services. John Mazzeo, DePaul University Available at: https://works.bepress.com/jmazzeo/32/
More informationSocio-economic Data for Drylands Monitoring The Living Standards Measurement Study Integrated Surveys on Agriculture
Socio-economic Data for Drylands Monitoring The Living Standards Measurement Study Integrated Surveys on Agriculture Alberto Zezza (Development Research Group, World Bank) www.worldbank.org/lsms Monitoring
More informationSmallholder Diaries Building the Evidence Base with Farming Families in Mozambique, Tanzania and Pakistan. Jamie Anderson Agrifin Webinar 24 May 2016
Smallholder Diaries Building the Evidence Base with Farming Families in Mozambique, Tanzania and Pakistan Jamie Anderson Agrifin Webinar 24 May 2016 Financial innovation for smallholder families Build
More informationWhat is the Impact of Drought on Prices? Evidence from Ethiopia
What is the Impact of Drought on Prices? Evidence from Ethiopia February 2018 This paper was prepared for the CSAE Conference to be held from 18-20 March 2018 at the University of Oxford Ruth Hill and
More informationWomen s Empowerment & Social Protection: cash transfers and beyond
Women s Empowerment & Social Protection: cash transfers and beyond Ana Paula De la O-Campos, Benjamin Davis & Silvio Daidone Food and Agriculture Organization-UN Malawi: Investing in Children and Women
More informationGlobal Strategy. Session 1.2: Minimum Set of Core Data Items. Module 1: Sampling in the Context of the Global Minimum Set of Core Data Items
Global Strategy IMPROVING AGRICULTURAL AND RURAL STATISTICS IN ASIA PACIFIC Module 1: Sampling in the Context of the Global Minimum Set of Core Data Items Session 1.2: Minimum Set of Core Data Items 13
More informationMyanmar s Rural Transformation:
Myanmar s Rural Transformation: Emerging evidence of rapid structural change Ben Belton (Michigan State University) Food Security Policy Project University of Sydney, Sydney Southeast Asia Centre 15 February,
More informationWFP in Bangladesh 2011 in Review
Fighting Fighting Hunger Hunger Worldwide Worldwide WFP in Bangladesh 2011 in Review West Darfur, Sudan Food Security Monitoring, ruary FEBRUARY Executive Summary The overall food security situation deteriorated
More informationSector Dialogues Beneshangul Gumuz region
FTA-SA regional partnership meeting June 2017 Sector Dialogues Beneshangul Gumuz region Sector data were collected by Social Accountability Implementing Partners in April 2017. Data graphs and tables are
More informationEl Salvador P4P Country Programme Profile
El Salvador Country Programme Profile Strategy El Salvador s smallholder farmers face a familiar set of barriers to market access: few options for marketing their produce, limited financial capacity to
More informationCOCOA LIFE COTE D IVOIRE NEEDS ASSESSMENT. Executive summary
COCOA LIFE COTE D IVOIRE NEEDS ASSESSMENT Executive summary April 2015 1. The purpose of the needs assessment A needs assessment is carried out for each Cocoa Life origin in the early stages of program
More informationDecent rural employment for food security in Tanzania
FAO DRE Capacity development workshop Morogoro, Tanzania, May 2012 Decent rural employment for food security in Tanzania Monika Percic International National Programme Coordinator Why MORE AND BETTER JOBS
More informationOn average, households spend 62 percent of their income on food, which is a slight increase compared to November 2010 (57 percent).
WFP Food Security Monitoring System (FSMS) Round 9 (February 2011) North Darfur State Main Findings The proportion of food secure households in the IDP category has increased compared to February 2010.
More informationSocioeconomic Characteristics of Smallholder Rice Production in Ethiopia
Socioeconomic Characteristics of Smallholder Rice Production in Ethiopia Minilik Tsega Dawit Alemu Shiratori Kiyoshi Research Report 100 የ ኢትዮጵያ የ ግብርና ምርምር ኢን ስቲትዩት Ethiopian Institute of Agricultural
More informationAGRICULTURAL SAMPLE SURVEY 2004/05 [1997 E.C.] VOLUME II
FEDERAL DEMOCRATIC REPUBLIC OF ETHIOPIA CENTRAL STATISTICAL AUTHORITY AGRICULTURAL SAMPLE SURVEY 2004/05 [1997 E.C.] VOLUME II REPORT ON LIVESTOCK AND LIVESTOCK CHARACTERISTICS (PRIVATE PEASANT HOLDINGS)
More informationAgriProfit$ Economics and Competitiveness. The Economics of Sugar Beet Production in Alberta 2008
AgriProfit$ Economics and Competitiveness The Economics of Sugar Beet Production in Alberta 2008 AGDEX 171/821-5 December, 2009 THE ECONOMICS OF SUGAR BEET PRODUCTION IN ALBERTA 2008 G. Nabi Chaudhary
More informationMalika Abdelali-Martini
Empowering Women in the Rural Labor Force with a focus on Agricultural Employment in the Middle East and North Africa (MENA) Malika Abdelali-Martini International Center for Agricultural Research in the
More informationTanzania National Panel Survey LSMS-ISA: Market Access
EPAR Brief No. 196 June 12, 2012 Tanzania National Panel Survey Living Standards Measurement Study- Integrated Surveys on Agriculture MARKET ACCESS Professor Leigh Anderson, Principal Investigator Associate
More information100% increase in Smallholder Productivity and Income in support of. An End to Rural Poverty: Double Small-scale Producer Incomes & Productivity
COMPENDIUM - FINAL REPORT ZERO HUNGER CHALLENGE WORKING GROUPS 100% increase in Smallholder Productivity and Income in support of An End to Rural Poverty: Double Small-scale Producer Incomes & Productivity
More informationPatterns of Agricultural Production among Male and Female Holders: September Leulsegged Kasa. Gashaw Tadesse Abate. James Warner.
Patterns of Agricultural Production among Male and Female Holders: Evidence from Agricultural Sample Surveys in Ethiopia September 2015 Leulsegged Kasa Gashaw Tadesse Abate James Warner Caitlin Kieran
More informationNepal. Fighting Hunger Worldwide. mvam Methodology. 1 Nepal Methodology Note
Fighting Hunger Worldwide Nepal mvam Methodology Survey design: While developing a survey methodology that is designed to produce representative estimates, the ultimate sampling units need to be selected
More informationContribution of Agribusiness to the Magic Valley Economy, 2010
CIS 1193 Contribution of Agribusiness to the Magic Valley Economy, 2010 by S. Hines, J. Packham, and G. Taylor Introduction Irrigation has transformed the Magic Valley desert (Cassia, Lincoln, Minidoka,
More informationRETAIL TRADE Workforce Demographics
RETAIL TRADE Workforce Demographics Maryland Department of Labor, Licensing and Regulation Division of Workforce Development Office of Workforce Information and Performance 1100 N. Eutaw Street, Room 316
More informationSurvey Expert to provide assistance for the Randomized rural household survey Scope of Work (SOW)
AgResults Kenya On-Farm Storage Pilot Survey Expert to provide assistance for the Randomized rural household survey Scope of Work (SOW) 1. Consultant Name TBD 2. Period of Performance TBD 3. Level of Effort
More information[ASK FOR THE PRICE OF EACH OF THE FOLLOWING ITEMS AS CHARGED BY THE MOST COMMON PLACE OF PURCHASE (TYPICALLY THE CLOSEST LOCATION]
CLUSTER ID REPUBLIC OF ZAMBIA MINISTRY OF COMMUNITY DEVELOPMENT, MOTHER AND CHILD HEALTH MCP 36 Month Follow-up Survey in Luwingu and Serenje Districts COMMUNITY QUESTIONNAIRE 2014 IDENTIFICATION PARTICULARS
More information2006 Iowa Farm Costs. and Returns File C1-10. Ag Decision Maker. Definition of Terms Used
2006 Iowa Farm Costs Ag Decision Maker and Returns File C1-10 The farm record data utilized in this report were obtained from the Iowa Farm Business Associations. The average of all farms in each table
More informationETHIOPIA MONTHLY MARKET WATCH
ETHIOPIA MONTHLY MARKET Highlights In, country level year to year general inflation rate increased by 7.8 percent; food inflation by 5.1 percent and non-food by 10.9 percent. The total price index of bread
More informationIt Increasing the Health and Nutritional Outcomes of Rwanda s One Cow per Poor Family from a Gender Perspective ion Lab for
It Increasing the Health and Nutritional Outcomes of Rwanda s One Cow per Poor Family from a Gender Perspective ion Lab for Kathleen Earl Colverson, Ph.D. Feed the Future Innovation Lab for Livestock Systems,
More informationAgriProfit$ Economics and Competitiveness. The Economics of Sugar Beet Production in Alberta 2007
AgriProfit$ Economics and Competitiveness The Economics of Sugar Beet Production in Alberta 2007 AGDEX 171/821-5 December, 2008 THE ECONOMICS OF SUGAR BEET PRODUCTION IN ALBERTA 2007 G. Nabi Chaudhary
More informationAfrican Medical and Research Foundation in Ethiopia
African Medical and Research Foundation in Ethiopia Final Evaluation to Access to Water, Sanitation and Hygiene Promotion Project, Gullele Sub City, District-5, Addis Ababa, Ethiopia BY: CONCRESCENCE FOR
More informationIntegrating Nutrition and Food Security programming For Emergency response and Resilience Building
Integrating Nutrition and Food Security programming For Emergency response and Resilience Building SECTION 1: OVERVIEW. Case Study / Sharing Good practices Global Villages (Formerly CHF), Save the Children,
More informationEvaluation Consultancy Terms of Reference
Evaluation Consultancy Terms of Reference Title: Zimbabwe Humanitarian Response 2015/16 1. Background CARE International in Zimbabwe is implementing an Emergency Cash-First Response to Drought- Affected
More informationModule 1: Conceptual framework: gender issues and gender analysis approaches
Module 1: Conceptual framework: gender issues and gender analysis approaches In this module, you will: explore the definitions of gender and sex ; understand what the key gender issues are in agriculture
More informationDeterminants of changes in youth and women agricultural labor participation in. selected African countries. Eugenie W. H. Maiga
Determinants of changes in youth and women agricultural labor participation in selected African countries Eugenie W. H. Maiga Assistant Professor, Université de Koudougou, Burkina Faso eugeniemaiga@gmail.com
More informationImpact of Conflicts on Role of Rural women s Household in Food Security (West Darfur Returnee s Area, Sudan)
Quest Journals Journal of Research in Humanities and Social Science Volume 4 ~ Issue 11 (2016) pp: 89-93 ISSN(Online) : 2321-9467 www.questjournals.org Research Paper Impact of Conflicts on Role of Rural
More informationAltarum Institute Survey of Consumer Health Care Opinions
Altarum Institute Survey of Consumer Health Care Opinions Fall 2011 By Wendy Lynch, Ph.D. and Brad Smith, Ph.D. Co-Directors, Altarum Center for Consumer Choice in Health Care Table of Contents I. Introduction
More information